code: def _is_log_scale(trials: list[FrozenTrial], param: str) -> bool:
      for trial in trials:
          if param in trial.params:
              dist = trial.distributions[param]
  
              if isinstance(dist, (FloatDistribution, IntDistribution)):
                  if dist.log:
                      return True
  
      return False
  
file_path: optuna/optuna/visualization/matplotlib/_utils.py
imports: from __future__ import annotations
  from optuna._experimental import experimental_func
  from optuna.distributions import CategoricalDistribution
  from optuna.distributions import FloatDistribution
  from optuna.distributions import IntDistribution
  from optuna.trial import FrozenTrial
  from optuna.visualization.matplotlib import _matplotlib_imports
label_desc: Use image node_id 2 for calling a global function with example usage: _is_log_scale(trials, param) and returns: False, True